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Can we create minds from machines?

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Erik Larson asks.

Erik J. Larson is a Fellow of the Technology & Democracy Project at Discovery Institute, and he is Science and Technology Editor at The Best Schools.org. He works on issues in computational technology and intelligence (AI). He is presently writing a book critiquing the overselling of AI. He earned his Ph.D. in Philosophy from The University of Texas at Austin in 2009. His dissertation was a hybrid that combined work in analytic philosophy, computer science, and linguistics and included faculty from all three departments.

Larson’s Ph.D. dissertation served as the basis for the writing of a provisional patent on using hierarchical classification techniques to locate specific event mentions in free text. His work on supervised machine learning methods for information extraction and natural language processing (NLP) helped him found a software company in 2007 dedicated to research and development on classifying blogs and other web text online. Larson wrote several successful proposals to the Defense Advanced Research Projects Agency (DARPA) and was awarded over $1.7 Million in funding to perform cutting-edge work in AI. His company was based in Austin, Texas and Palo Alto, California.More.

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Thought provoking and educating. A very good talk. EugeneS
Brainstorming question for those who know: How successfully could abductive reasoning be programmed? For example, Dr. Larson gave the example of observing that the street is wet and then inferring to the best explanation of why it would be wet. Given that there are multiple competing explanations (rain, fire truck, kids playing with the fire hydrant, street sweeper, hose, broken pipe, etc.), he noted that it is not possible to directly program abductive reasoning. However, wouldn't it be possible, at least in principle, to program in those various causal explanations (perhaps based on big data -- another area he discusses), and then have the AI evaluate the likelihood of those competing explanations to arrive at an inference to the best explanation -- just like we do with our human intelligence? What limitations, if any, would there be on such an approach to handling abductive problems? Stated perhaps in other words, can an abductive problem be reduced, at some level, to a set of deductive and inductive problems which, themselves, are easier to handle programatically? Eric Anderson
Excellent presentation and well worth it. A bit long, but speed up to 1.25 or 1.5 and sit back and enjoy. Particularly good discussion toward the end about abduction and its relationship to AI. The "inference to the best explanation" approach that we use time and again in our everyday lives. Eric Anderson
Funny about the hammer. Its all just memory for machines. SO can memory mimic intelligence? I mean actually compare memories to come up with new unmemorized data. ! Intelligence is about conclusions from data. With people we figure everything out and that means conclusions are not already memorized. Intelligence is about new, right/wrong, conclusions . Computers only deal with conclusions already settled by the trail of the logic of data. Nobody in there to be right or wrong. if you can't be wrong then your not using your intelligence. Robert Byers
The video is worth watching, and certainly so if one is involved in the development of artificial intelligence. Not that I think there is any such thing. There isn't. Computers are indeed very cleverly designed, very intricate tools, but remain merely tools with no more intelligence than a hammer, with no more awareness of the meaning of the results they have been used to calculate than an abacus has of the result we obtained from it. No matter how brilliantly and intricately we manage electron flow, neither the electrons, nor the CPU components we use to manage their flow, nor any of the other items of which a computer is comprised, are any more aware of what is going on than is a hammer. harry

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